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This is a follow-up to the issue raised in https://github.com/scikit-learn/scikit-learn/issues/29554. However, I recall other issues raised for CV estimator in general.
So the context is the follow…
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# Class imbalance and classification metrics with aircraft wildlife strikes | Julia Silge
Handling class imbalance in modeling affects classification metrics in different ways. Learn how to use tidym…
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Approach I'd take :- 1. Utilizing 5 models such as DenseNet121 , Xception, VGG16, ResNet50, and InceptionV3 for image classification.
2. Applying data augmentation (rotation, zooming, flipping,…
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The xgboost, RF and NN models all have different ways to handle imbalanced classification datasets by using class-specific weights in their loss functions; but we currently only support this for NN mo…
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I'm working on a text classification problem similar to the sentiment_imdb problem, with 4 classes. My training set is highly imbalanced and I'd like to use balanced class weights for training. What's…
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Hello,
I'd like to reproduce the results.
I just want to make sure what are the correct params: how can I know what are the exact params to be used for each scenrio? are the default ones in scrip…
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# Building a multiclass classification model | Practical Cheminformatics
Data cleaning, adding structures to PubChem data, building a multiclass model, dealing with imbalanced data
[https://patwalte…
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Consider the table displaying basics of each issue type in:
docs/source/cleanlab/datalab/guide/table.rst
![Screen Shot 2024-06-03 at 11 09 21 PM](https://github.com/cleanlab/cleanlab/assets/139063…
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Hello gents,
I was hoping I can get a second opinion about a situation I am facing while using setfit for a multi class classification use case.
The dataset is small with 255 samples across 9 clas…
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One way to handle imbalanced classes via downsampling in AutoGluon with bagging would be for each bagging fold to be comprised of: a randomly under-sampled subset of majority class (drawn without repl…